Soil horizon mapping and textural classification using micro soil electrical resistivity measurements: case study from Ado-Ekiti, southwestern Nigeria

2018 ◽  
Vol 11 (12) ◽  
Author(s):  
A. B. Eluwole ◽  
M. O. Olorunfemi ◽  
O. L. Ademilua
Keyword(s):  
Electrical Resistivity ◽  
Soil Horizon ◽  
Southwestern Nigeria ◽  
Resistivity Measurements ◽  
Soil Electrical Resistivity

scholarly journals Can Soil Electrical Resistivity Measurements Aid the Identification of Forest Areas Prone to Windthrow Disturbance?

Forests ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 234
Author(s):  
Marián Homolák ◽  
Erika Gömöryová ◽  
Viliam Pichler
Keyword(s):  
Electrical Resistivity ◽  
Soil Properties ◽  
Clay Content ◽  
Field Measurements ◽  
Beech Forest ◽  
Root Penetration ◽  
Predictive Tool ◽  
Entire Study ◽  
Resistivity Measurements ◽  
Soil Electrical Resistivity

This study investigates how certain forest soil properties influence the propensity of beech forests to windthrow disturbances. The field measurements of soil electrical resistivity were carried out in an old-growth natural beech forest where the soil has developed from Cainozoic sedimentary rock with mudstone–claystone stratigraphy. In 2014, the forest was hit by a severe windstorm, and dispersed windthrow occurred at certain plots. Apparent electrical resistivity measurements were performed to investigate whether some soil properties could influence the forest trees’ predisposition to windthrow. The increases in the clay content and soil bulk density below 30 cm were associated with weathered claystone and mudstone, which created a physiological barrier for deeper root penetration. The result of the χ 2 test suggested that the windthrown spots were not distributed evenly over the entire study area. They were mainly concentrated over approximately 50% of the area, and their positions coincided with low resistivity values, indicating low soil skeleton content, high clay content and soil moisture. Therefore, electrical resistivity tomography could be considered a useful predictive tool for reducing the risk of natural disturbances by preventive forest management.

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